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The position is part of the ERC-funded project "INFLUENCE: Influence-based Decision-making in Uncertain Environments" which aims to significantly scale up decision making for complex systems. For instance, we will develop techniques to enable city-scale coordination of traffic lights control or better autonomous warehousing (e.g., order picking) with large teams of robots.
You will work in a team of several postdocs and PhD students. This position will focus on learning compact descriptions of 'influence', which describe how a sub-problem is affected over time, by building on state-of-the-art (deep) machine learning techniques.
The ideal candidate:
- has a Master’s degree in computer science, math, or physics.
- has excellent math skills.
- took at least one machine learning course.
- has demonstrable experience with state-of-the-art deep learning frameworks, such as tensorflow.
- has experience in C/C++
- is fluent in English
- is self motivated; has the drive to succeed individually
- is a team player; has the desire to succeed as a team
Fixed-term contract: 4 Years.
TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children’s Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.
As a PhD candidate you will be enrolled in the TU Delft Graduate School. TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit www.tudelft.nl/phd for more information.
The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) is known worldwide for its high academic quality and the social relevance of its research programmes. The faculty’s excellent facilities accentuate its international position in teaching and research. Within this interdisciplinary and international setting the faculty employs more than 1100 employees, including about 400 graduate students and about 2100 students. Together they work on a broad range of technical innovations in the fields of sustainable energy, telecommunications, microelectronics, embedded systems, computer and software engineering, interactive multimedia and applied mathematics.
The department of Intelligent Systems (INSY) conceptualizes computer science methodologies to sense, abstract, learn, reason, elicitate and adapt data and their meaning in ways that respect human values in order to increase human effectiveness in well-being and social innovation. At the heart of the department is therefore the research and teaching in computer science theory, algorithms and solutions for information processing systems that support humans (e.g. robotics), new products (e.g. internet services), and science (e.g. biology).
The Interactive Intelligence group focuses on interaction of users with intelligent systems. In particular we have a strong track record on the development of smart interactive agents. Such agents possess capabilities including learning, reasoning, social skills, emotions, and norms and can interact with humans. These agents typically function as coach, artificial actor, or companion, and are used in a wide variety of applications including therapy, health and entertainment.